In a cloud computing environment, computing is delivered as a service rather than a product, whereby shared resources, software and information are provided to computers and other devices as a metered service over a network, such as the Internet. In such an environment, computation, software, data access and storage services are provided to users that do not require knowledge of the physical location and configuration of the system that delivers the services.
The workloads of the cloud computing environment are supported by many types of hardware and software in the cloud computing environment which may require updates to enable them to operate correctly. For example, hardware components, such as network switches, fiber optic devices, physical compute machines and power distribution units, need to be updated to enable them to continue to operate correctly. Software components, such as operating systems, middleware applications (e.g., message queues, databases, application servers), user application binaries and cloud controller logic, may also need to be updated to enable them to continue to operate correctly. Unfortunately, such updates to these hardware and software components may result in disruptive behavior, such as requiring hardware components (e.g., physical compute machines) to be taken offline to complete their update. As a result of such disruptive behavior, the workloads running on those components have to be migrated to redundant systems during the maintenance window so that the components can be completely updated.
However, such migrations require a significant amount of time, resources and planning During a migration of a workload, the active memory and possibly the storage unit, such as a virtual disk(s), of the target workload are transferred over the network in real time to a different hardware component in the cloud computing environment. Such a process may be lengthy in time since the resources utilized by the workloads may easily be on the order of many gigabytes. These transfers reduce network and target workload throughput since the memory and disk modifications need to be resolved during the migration. If, however, the number of these migrations for the workloads could be reduced during the cloud maintenance operations, then the performance penalty incurred to both the infrastructure and the workload could be reduced during the cloud maintenance operations.